University of Cambridge > Mathematics > Statistical
    Laboratory > Richard Weber > Optimization
    
     This material is provided for students, supervisors (and others) to freely use
    in connection with this course. Copyright remains with the author.
    
      Optimization IB
    
 Constraints for problem P
    
      This is home page for a course of 12 lectures to first and second year Cambridge mathematics students.
    
    There is a more modern version of this course here.
    
      Each lecture is as self-contained as possible and has course notes amounting to four or five
      A4 pages. Click here for the table of contents.
    
    
      I have also made additional notes about things I said in lectures and questions students
      have asked.
    
    
      There is a single examples sheet and a file of exam questions.
      Students should receive two supervisions on the examples sheet. There are two recommended
      books. If you enjoy this course then you should consider related courses in Part II
      and other items of interest.
    
    
      Course notes
    
How to view and print: There are 56 pages of notes available as a pdf file. The notes are formatted as two
side-by-side pages per A4 sheet.
    
      - 
        O.pdf (119K) has all the above in a single file
      
 
    
    
      Where to collect photocopies of the notes: You can find copies of notes by using this map to locate the
      Statistical Laboratory pigeonholes. 
    
    
      
    
    
      Examples sheets
    
There is a single examples sheet, available as a pdf file of 6 pages. The topics that the questions cover
    appear in the same order as topics are covered in lectures and you will find a recommendation on the sheet
    concerning the work you should do for your supervisions. Viewing and printing is identical as for the notes above.
    
    
      Overheads
    
    
      I include a small (non-examinable) digression half way through each lecture.
    
    
      Topics I have covered are:
    
    
      - set partitioning
      
 
      - job scheduling
      
 
      - optimal electricity generation and distribution
      
 
      - insects as optimizers
      
 
      - project assignment in CUED
      
 
      - examples of very large LPs
      
 
      - how large an LP can we solve?
      
 
      - on-line bin packing
      
 
      - airline luggage
      
 
      - MacDiet problem
      
 
      - hanging chain
      
 
      - hanging springs puzzle
      
 
      - string covering (an open problem)
      
 
      - Braess's paradox
      
 
      - more examples of very large LPs
      
 
      - 
        rendezvous problem
      
 
    
These examples and other material are included in this file of overhead projector slides.
    Additional notes
    Here are some additional notes which summarise things I said in lectures and which do not
    appear in the printed notes. I have also made notes about questions that students asked, either in lectures or by
    coming up to me afterwards.
    
      Exam questions
Here is single fille of all Tripos questions on Optimization for the years 2004-2011
    
      This file has exam questions from 1985-1997.
    
    
    
      Recommended books
    
    
      - Bazaraa, M., Jarvis, J. and Sherali, H., Linear Programming and Network Flows. second edition, 1990, Wiley.
      
 
      - Luenberger, D., Introduction to Linear and Non-Linear Programmings, second edition, 1984, Addison-Wesley.
      
 
    
    
      Related courses
    
There are two courses in Part II that build on what students learn in this course. In Part IIA there is
    Algorithms and Networks. In Part IIB there is Optimization and Control.
    
    
    
      Other items of interest
    
    
      - A Pascal program implementing the simplex algorithm.
      
 
      - An executable program lp_solve that you can easily run on a PC under DOS to compute the solution to linear
      programming problems and integer linear programming problems. Click here for an
      explanation of how to use the program and instructions on downloading it to your computer.
        
          Spreadsheet programs like Microsoft Excel and Quattro Pro also contain LP solvers that are good for up to
          about 200 variables.
        
       
      - An interactive diet solver that will
      find your "optimal" diet based on a list of foods you tell it you are willing to eat.
        
          The goal of the diet problem is to find the cheapest combination of foods that will satisfy all the daily
          nutritional requirements of a person. The problem is formulated as a linear program where the objective is to
          minimize cost and meet constraints which require that nutritional needs be satisfied. We include constraints
          that regulate the number of calories and amounts of vitamins, minerals, fats, sodium and cholesterol in the
          diet. The mathematical formulation is simple, but you will find out by running the model that people do not
          actually choose their menus by solving this model. The diet problem is one of the first optimization problems
          to be studied back in the 1930's and 40's. It was first motivated by the Army's desire to meet the
          nutritional requirements of the field GI's while minimizing the cost. Read more about the amusing history of the diet problem.
        
       
      - 
        NEOS Guide to Optimization including an overview
        of optimization, case studies, test problems, and much, much more. Well worth looking at!
      
 
      - If you are interested in learning about modern interior
      point methods for solving LP problems, read here.
      
 
      - Here are some biographical notes about George
      Dantzig, the originator of the simplex method, on the occasion of his 80th birthday.
      
 
    
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    Last modified: 17 Janaury 2007